Department of Electrical Engineering, Stanford University, Stanford, CA 94035-6019, USA.
Health Care Manag Sci. 2011 Jun;14(2):174-88. doi: 10.1007/s10729-011-9150-2. Epub 2011 Mar 5.
Many models of infectious disease ignore the underlying contact structure through which the disease spreads. However, in order to evaluate the efficacy of certain disease control interventions, it may be important to include this network structure. We present a network modeling framework of the spread of disease and a methodology for inferring important model parameters, such as those governing network structure and network dynamics, from readily available data sources. This is a general and flexible framework with wide applicability to modeling the spread of disease through sexual or close contact networks. To illustrate, we apply this modeling framework to evaluate HIV control programs in sub-Saharan Africa, including programs aimed at concurrent partnership reduction, reductions in risky sexual behavior, and scale up of HIV treatment.
许多传染病模型忽略了疾病传播所依赖的潜在接触结构。然而，为了评估某些疾病控制干预措施的效果，纳入这种网络结构可能很重要。我们提出了一种疾病传播的网络建模框架和一种从现成数据源推断重要模型参数（如控制网络结构和网络动态的参数）的方法。这是一个通用且灵活的框架，广泛适用于通过性接触或密切接触网络来建模疾病的传播。为了说明问题，我们应用这个建模框架来评估撒哈拉以南非洲的艾滋病毒控制项目，包括旨在减少同时性伴侣、降低危险性行为和扩大艾滋病毒治疗的项目。
